Method, system, and storage medium for facilitating excess inventory utilization in a manufacturing environment

ABSTRACT

An exemplary embodiment of the invention relates to a method, system and storage medium for utilizing excess inventory comprising parts used in end products. The method comprises: translating sales specific terminology describing end products into bill of material terminology describing parts used in end products via a bill of material structure; and, utilizing the bill of material structure, determining an optimal build plan for end items that, if built, would consume a desired quantity and/or type of excess inventory. The invention also comprises a system and storage medium.

FIELD OF THE INVENTION

[0001] The present invention relates generally to inventory management.More particularly, the present invention relates to a method, system,and storage medium for facilitating excess inventory utilization in amanufacturing environment.

BACKGROUND OF THE INVENTION

[0002] In a manufacturing environment products are built that oftencomprise many possible configurations while sharing some common lowerlevel assemblies and parts in their bills of material. Due to factorssuch as market fluctuations and other unanticipated environmentalchanges, it is not uncommon for a manufacturer to be left with excessinventory on certain parts. These parts may include those that areordered but not yet received in which the manufacturer incurs liabilityfor cancellation, or they may be parts held by a contract manufacturer,or involve other similar types of situations.

[0003] Surplus/excess inventory can, be problematic for a manufactureras it can increase costs and reduce profits. Inventory specialists arecontinually working to reduce inventory levels by finding ways toshorten the pipeline and reduce lead times. Attempts at solving thesurplus/excess inventory problem include developing a build plan for endproducts that would consume as many of these surplus/excess parts aspossible. This build decision has been solved in the past in a manualfashion by investigating individual choices one at a time. Not only isthis labor intensive, but when an excess parts could be used on severalalternative saleable items, each of which might consume variousquantities of other excess parts, the problem becomes too complex forthe manual approach.

[0004] What is needed is a method of assessing existing surplus/excessparts inventories and developing an optimum build plan for end productsthat would consume these parts.

SUMMARY OF THE INVENTION

[0005] An exemplary embodiment of the invention relates to a method,system and storage medium for utilizing excess inventory comprisingparts used in end products. The method comprises: translating salesspecific terminology describing end products into bill of materialterminology describing parts used in end products via a bill of materialstructure; and, utilizing the bill of material structure, determining anoptimal build plan for end items that, if built, would consume a desiredquantity and/or type of excess inventory. The invention also comprises asystem and storage medium.

BRIEF DESCRIPTION OF THE DRAWINGS

[0006]FIG. 1 is a block diagram of an exemplary system for facilitatingexcess inventory utilization management.

[0007]FIG. 2 is a graphical depiction of a sample bill of materialstructure used in a translation process of the inventory utilizationtool.

[0008]FIG. 3 is a flowchart of a process for assisting an inventoryplanner in determining an optimum build plan in an exemplary embodiment.

DETAILED DESCRIPTION OF THE INVENTION

[0009]FIG. 1 is a block diagram of an exemplary system for facilitatingexcess inventory utilization in accordance with an exemplary embodimentof the invention. Excess parts files (also referred to herein as excessinventory files) 106 are provided by manufacturing/inventory personneland contain lists of any excess/surplus (herein referred to as ‘excess’)parts along with the quantity in excess. Manufacturing process datafiles 107 may include data relating to yields, cycle times, usage rates,capacities, alternative parts, and other desirable information. Datafrom these files 106 and 107 are submitted to a Manufacturing ResourcePlanning (MRP) engine 102 that employs the inventory utilization tool104 of the invention. BOM files in database 108 store parts lists forsaleable end items. Saleable end items refers to parts, products,subassemblies, and includes any item that can be produced and sold forrevenue by a manufacturing entity in order to use up excess inventory.The inventory utilization tool 104 comprises a shell script forgenerating new BOM data structures as will be discussed further herein.A reports database 110 is included in FIG. 1 and stores reportsgenerated by the inventory utilization tool 104 for analysis and reviewby specified inventory specialists (also referred to herein as inventoryplanners).

[0010] Operation of the inventory utilization tool from the perspectiveof an inventory planner of a manufacturing entity will now be describedwith reference to FIGS. 2 and 3. In an exemplary embodiment, theinventory utilization tool employs a method comprising a translationsegment and a solution segment.

[0011] For products (also referred to herein as saleable end items) thatare fairly complex, and the configuration choices numerous, a simplifiedway of describing them may be helpful so that customers and salespeopleof the manufacturing entity have an easier time deciding on and orderingwhat they want. This ‘sales nomenclature’ involves a mapping process attime of order placement whereby products are transcribed fromsales-specific terminology to bill of material part numbers (referred toherein as ‘manufacturing nomenclature’). The mapping is preferablymany-to-many, and may often be order dependent (i.e., one-way mapping).

[0012] For example, in placing an order for an upgraded automobileinterior, the dealer may specify a code ‘DLUX’. This code is the samefor model X (economy car), model Y (luxury sedan), or model Z (sportsutility vehicle). However, the part numbers required for that order(i.e., part numbers that are needed in order for manufacturing tofulfill the order) are dependent on the code ‘DLUX’ as well as the modelnumber of the vehicle (i.e., model X, Y, or Z).

[0013] There are two decisions this method supports: (1) which saleableend items to produce out of the excess inventory in order to use up asmuch inventory as possible while incurring minimal costs for purchasingadditional lower-level parts needed to ‘square up sets’ and produce theend items; and (2) how to express the choice of saleable end items insales nomenclature, even though the available inventory is expressed inmanufacturing nomenclature.

[0014] The translation segment takes information presented inmanufacturing terms and translates it into sales terms. Productdescriptions of saleable end items using sales nomenclature are referredto herein as ‘features’. Saleable end items include items which can besold for revenue. A personal computer is one example of a saleable enditem. Some features may require the same part numbers, regardless ofother aspects of the order (e.g., a replacement headlight might bereferred to as “HDLT” and would include a distinct set of parts tobuild). These features are referred to herein as ‘simple features’.

[0015] Features that require just one other piece of information inorder to know the exact part numbers required are referred to as‘plus-one simple’ features. Plus-one simple features become ‘simple’with the addition of one piece of data. For example, an automobileexhaust system requires knowing the state in which the vehicle will beregistered due to differing emission controls among the states. Theexhaust system may be referenced as ‘EXHST’ with a plus-one feature forthe state.

[0016] The bill of materials structure for plus-one simple features canbe built by making a copy of the feature for each distinct value of theadditional information (i.e., distinct in the sense that different partsare required). For example, if California required different parts inits exhaust systems but all other states had the same parts, twosaleable assembly parts would be created out of the one feature asillustrated in FIG. 2.

[0017] This concept may be extended to ‘plus-two simple’ features,‘plus-three simple’ features, and so on. The saleable assembly partscreated out of a ‘plus-k simple’ feature would be k-tuples, resulting inpotentially extensive proliferation of similar bill records as ‘k’ getslarge.

[0018] This same approach may extend to features whose translationdepends on the presence of other features. For example, a deluxeinterior (described as one feature) coupled with a stereo (described asa second feature) may require a different dashboard cover (identified bya different part number) than a deluxe interior without that stereo.

[0019] In practice, it makes sense to capture those features which areas simple as possible, yet make up the vast majority of all features.Plus-one or plus-two simple features may be all that are necessary todescribe these features. Any other or more complex features could beomitted from the build-out decision, unless they can be expressed in adifferent way.

[0020] Once the new BOM structure is established, the tool assists theMRP engine in the solution segment as described herein.

[0021] The decision of what to build out of excess parts requires a wayto distinguish value between choices of saleable end items, oftenexpressed as either revenue or profit. This decision is very similar tothe decision of what can best be built out of a set of constrainedparts. This latter problem has been modeled in various ways and solvedby linear programming (LP) tools as well as various heuristics (e.g.,local search techniques), artificial intelligence techniques (e.g.,genetic algorithms, neural networks, tabu search, etc.), and non-linearoptimization (e.g., gradient search techniques). One such approachinvolves an optimization engine which uses a set of subroutines calledthe Watson Implosion Tool (WIT). This approach is the subject of U.S.Pat. No. 5,630,070, entitled “Optimization of Manufacturing ResourcePlanning”. The model of the present invention differs in that an apriori expression of demand that a manufacturer is trying to satisfy isnot needed. Also, a manufacturer may wish to express an upper limit(referred to as ‘k’) on how much to spend for additional materials inorder to use up one dollar of excess inventory. Further, revenues perunit of a saleable item (i.e., prices) may be volume-dependent, a factoraddressed by the present invention. Finally, higher-level (e.g.,assembly) items in excess may also be disassembled to create and thenreuse supply of these low-level parts in other products.

[0022] The method involves getting all data related to the manufacturingprocess (e.g., yields, cycle times, usage rates, capacities, alternateparts, etc.) from manufacturing process database 107 or other similardata source and formulate constraints related to the usage of materialsin producing other materials, and eventually, saleable end items. If norevenue data are available, the choice amongst saleable end items can bemade by using a formula, ‘k’ times ‘ei’ (expressed as k*ei), as therevenue for item ‘i’ where ‘ei’ is the amount in dollars of excessinventory consumed when producing/selling one unit of item ‘i’. Thescalar factor ‘k’ referenced above may be set by a decision maker. Ei iscalculated by using a ‘pegging’ subroutine applied to a variant of theoriginal problem, where a dummy part is added as a component of allother parts, with usage rate set to the value of the part for those thatare excess inventory, and to zero otherwise. This step assists inbalancing two competing forces: how important is using up excess (at anycost) versus how important is it to not incur additional cost (forsquaring up sets). This balance is reflected through ‘k’, whichindicates how much one is willing to spend (in additional purchases) ata maximum in order to use of one dollar of excess. For example, amanufacturing entity may be interested in spending $1.00 for everydollar of excess inventory to be disposed. Alternatively, amanufacturing entity may be more interested in getting rid of inventoryand may choose to spend $3.00 to dispose of a $1.00 of excess inventory.The ‘k’ factor expresses this sensitivity between using up excess andminimizing additional spending.

[0023] In order to find the most desirable solution for a given value of‘k’, the problem may be modeled as a linear equation as follows.

Maximize profit=Revenue minus Cost

[0024] It will be noted that the cost to build a saleable end item isthe cost of all components where those in excess are considered free,and the revenue is ‘k’ times the excess consumed in building one enditem. This equation assumes that the price the marketplace would pay forthe item is not known. If actual prices are known, they can besubstituted for revenue in the above equation. Thus, using the scalingfactor, one can optimize how much excess to be consumed (e.g., setting‘k’ very large), or how little additional purchase required (e.g.,setting ‘k’ very small), or somewhere in between. Alternatively, ifmarket prices are available, they may be utilized in the equation inorder to optimize overall profit.

[0025] The optimization objective may be more general thanprofitability, for example, by factoring in a priority on the saleableend items that reflects how perishable they are, how easy they are tosell, how seasonable they may be, etc. By way of example and notlimitation, other optimization objectives may include or take intoaccount strategic objectives (e.g., a loss leader), special customerservice needs, or any other desired business purpose. This informationcan be most generally considered “business impact” information, whichcan be balanced with other factors such as the relative desirability ofbuilding end items, with the relative cost of additional purchasesneeded, and the benefit of consuming the excess inventory. It isgenerally known in the art that there are situations influencingproduction decisions beyond mechanical analysis of simple profitabilitydefined by revenue minus costs of an individual end item.

[0026] Note that this business impact can also vary over time and byvolume. For example, the company might be able to sell 100 units at$5,000 each but selling more than 100 units would only be possible ifthe price were dropped to $4,800. In this example, business impact wouldbe defined as profit (e.g., end product revenue minus the cost of partsin the associated BOM, cost of manufacturing, etc.), and the revenuesfor saleable end items would be defined by piece-wise linear functionsof the volume sold. Since some of the parts in excess inventory (as wellas the end products and end items to be made from such parts) may losevalue more quickly than others (i.e., more “perishable”), there may be ahigher priority associated with particular parts in excess inventory orend products which will in turn affect the optimization of the buildplan.

[0027] Similarly, the costs of additional purchase items may depend ontime or volume. Additionally, by treating an excess inventory item orpart as “saleable” (that is, it could be sold by itself, or built into ahigher-level product), one can also capture the dynamic oftime-dependent scrap value (perishability). Finally, some of the itemsrequired for building a saleable end item may be constrained (e.g., havean ‘infinite’ cost to acquire beyond a certain number of units). All ofthese considerations on ‘business impact’ can be taken into account infinding an optimal solution.

[0028] The optimization criteria used in the optimization are non-demandcriteria. Non-demand criteria are those criteria that can be assessedwithout having a demand statement associated with one or more endproducts. Demand statements are a quantity that is forecasted orconfirmed of how many end products can be sold. In many instances,demand statements are broken out over units of time (e.g., 10 of product‘X’ in January, 50 of product ‘Y’ in 2002). In configurable products,such as high end computer systems, it is difficult to develop demandstatements on every permutation. Examples of non-demand criteria are:utilizing the quantity or dollar value of inventory, minimizingadditional dollars spent to utilize quantity or dollar value ofinventory, maximizing profit of end items, taking into account otherbusiness criteria such as perishability, a loss leader, etc., oranything else that does not include a demand statement.

[0029] In MRP systems and other support tools for helping companiesdecide what to build, demand for end products is a critical, if not themost critical criteria for optimizing a build plan. The intent is toproduce where there is a known demand as represented by demandstatements for the end products that the business entity produces.

[0030] When focusing on surplus/excess parts inventory, the optimizationof the build plan will focus on criteria relevant to the surplus/excessinventory such as the quantity or dollar value of inventory consumed bythe build plan or the overall potential business impact of the endproducts produced. These decisions are initially made absent demandstatements and the build plan is assessed for ease of sale or as a guideto areas where steps should be taken to increase demand. In other words,the present invention assists in generating opportunities while existingMRP systems and support tools typically match supply to a proposeddemand for end products. One way of using the exemplary embodiment wouldbe to generate a number of possible build scenarios optimized usingnon-demand criteria and having marketing professionals do demandanalysis or other analysis to determine which of the opportunitiesidentified would be easiest to execute.

[0031] The process of utilizing the above optimization component in amanufacturing setting will now be described. Basic records and inputsare obtained at step 302. These include BOM, costs, revenue (ifavailable), inventory, and ei data. The tool sets k to zero and‘DemandVolumes’ to ‘Big M’ at step 304. ‘Big M’ refers to an initialupper limit in linear programing and is used as an initial solution(e.g., a demand to satisfy) in starting the optimization process. Thisvalue, or upper limit, is selected for the purpose of initiatingimplementation of the linear program only and does not reflect actual orspecific demand values (e.g., a random or arbitrary value). An implosiontool is used to find optimal available-to-sell (ATS) volumes forend-items at step 306. The saleability of ATS volumes are assessed atstep 308. If ATS volumes exceed saleability at step 310, then‘DemandVolumes’ for those items are decreased at step 312 and theprocess returns to step 306. Steps 306-308 are repeated until ATSvolumes are less than or equal to saleability. Aggregated availabilityis assessed at step 314. If aggregated availability is exceeded for anyitem groups at step 316, then demand volumes for items within this groupare decreased at step 318 and the process again returns to step 306;otherwise, the process continues at step 319 in which the consumption ofexcess items is assessed. If more excess needs to be consumed, then k isincremented at step 320 and the process returns to step 306. Steps306-319 may be repeated until there is no more excess requiringconsumption.

[0032] The present invention enables a manufacturer to pursue aconcerted effort in sales and to sell through items which will consumeexcess inventory. These efforts may include alternate channels (such ase-auctions or discount brokers), marketing campaigns, use as repairparts, etc. Furthermore, the approach to translating from manufacturinginto sales nomenclature has further applications to expressingavailable-to-promise (ATP) in terms meaningful to the sales force andcustomers.

[0033] As described above, the present invention can be embodied in theform of computer-implemented processes and apparatuses for practicingthose processes. The present invention can also be embodied in the formof computer program code containing instructions embodied in tangiblemedia, such as floppy diskettes, CD-ROMs, hard drives, or any othercomputer-readable medium, wherein, when the computer program code isloaded into and executed by a computer, the computer becomes anapparatus for practicing the invention. The present invention can alsobe embodied in the form of computer program code, for example, whetherstored in a storage medium, loaded into and/or executed by a computer ortransmitted over some transmission medium, such as over electricalwiring or cabling, through fiber optics, or via electromagneticradiation, wherein, when the computer program code is loaded into andexecuted by a computer, the computer becomes an apparatus for practicingthe invention. When implemented on a general-purpose microprocessor, thecomputer program code segments configure the microprocessor to createspecific logic circuits.

[0034] It will be evident to those skilled in the art that the presentinvention provides many improvements over the current state of the artof ratio planning. Data from a variety of systems and locations is beingcollected into a single database in order to provide a single,integrated repository for ratio planning data. The invention allowsratio planners to catalogue part numbers and models in order to providesome structure and meaning to the thousands of seemingly random partnumbers. The cataloging provides an easy way to pull informationtogether for reports. Additionally, the invention provides the ability,through the use of pre-defined reports, to generate reports very quicklyand with a minimum of computer database expertise on the part of theratio planner. The invention is well suited for both small manufacturerswith relatively few ratios as well as very large manufacturers with tensof thousands of ratios.

[0035] While the invention has been described with reference toexemplary embodiments, it will be understood by those skilled in the artthat various changes may be made and equivalents may be substituted forelements thereof without departing from the scope of the invention. Inaddition, many modifications may be made to adapt a particular situationto the teachings of the invention without departing from the essentialscope thereof. Therefore, it is intended that the invention not belimited to the particular embodiments for carrying out this invention,but that the invention will include all embodiments falling within thescope of the appended claims.

What is claimed is:
 1. A method for utilizing excess inventory in amanufacturing environment, said excess inventory comprising parts usedin end products, comprising: translating sales specific terminologydescribing said end products into bill of material terminologydescribing said parts used in end products via a bill of materialstructure; and utilizing said bill of material structure, determining anoptimal build plan for end items that, if built, would consume a desiredquantity and/or type of excess inventory.
 2. The method of claim 1,wherein said translating sales specific terminology into said bill ofmaterial terminology includes: classifying features associated with saidend items according to parts required to build said end items.
 3. Themethod of claim 2, wherein said classifying features associated withsaid end items includes: sub-classifying said features wherein a featureof an end item comprises more than one distinct set of parts.
 4. Themethod of claim 1, wherein said determining an optimal build planincludes: formulating constraints related to usage of parts in producingend items utilizing: data provided in said bill of material structure;and manufacturing process data resulting in at least one saleable enditem, comprising at least one of: costs; revenue data; inventory data;usage rates; yields; capacities; cycle times; and alternate parts; andoptimizing said constraints utilizing at least one of: heuristics;linear programming; artificial intelligence; and non-linearoptimization.
 5. The method of claim 4, wherein selecting an end itemfrom a list of saleable end items capable of consuming excess inventoryincludes: utilizing user-supplied pricing information to determine whichof said saleable end items, if built, would consume the most excessparts while requiring minimal additional expense.
 6. The method of claim4, wherein selecting an end item from a list of saleable items capableof consuming excess inventory comprises: applying an algorithmcomprising: k*ei; wherein k is a scalar factor referring to a selectablenumber operable for expressing an upper limit on how much to spend onadditional parts in order to use up one dollar of excess inventory; andwherein further, ‘ei’ represents an amount in dollars of excessinventory consumed when producing one unit of an item ‘i’.
 7. A methodfor utilizing excess inventory of parts, said parts used in end productsand having part identifiers, the method comprising: identifying anexcess inventory of parts comprising part identifiers and a quantityassociated with each part identifier; identifying potential end productsfor manufacture comprising a Bill of Materials (BOM) for each endproduct and where each BOM calls out at least one part identifier in theexcess inventory of parts; and determining a build plan comprising oneor more of the potential end products, the build plan optimized tospecific criteria and utilizing an amount of the excess inventory. 8.The method of claim 7 further comprising a cost value associated witheach part identifier and wherein the specific criteria comprise a scalarvalue representing a ratio of the dollar amount spent to purchaseadditional parts in order to consume one dollar's worth of the excessinventory.
 9. The method of claim 7 wherein the specific criteriacomprise maximizing the quantity of the excess inventory utilized. 10.The method of claim 7 further comprising a cost value associated witheach part identifier and wherein the specific criteria comprisemaximizing the total cost value of the excess inventory utilized. 11.The method of claim 7 wherein the specific criteria comprise maximizingthe quantity of the excess inventory utilized without exceeding aspecific dollar value of additional parts purchased to produce the buildplan.
 12. The method of claim 7 further comprising a cost valueassociated with each part identifier and wherein the specific criteriacomprise maximizing the total cost value of the excess inventoryutilized without exceeding a specific dollar value of additional partspurchased to produce the build plan.
 13. The method of claim 7 whereinthe specific criteria comprise minimizing the amount of additional moneyspent in order to utilize the excess inventory.
 14. The method of claim7 further comprising profitability information on each potential endproduct and wherein the specific criteria comprise maximizing theoverall profit of the build plan.
 15. The method of claim 7 furthercomprising business impact information and wherein the specific criteriacomprise taking into account the business impact of the build plan. 16.The method of claim 7 wherein the build plan is determined using anoptimizing solver.
 17. The method of claim 16 wherein the optimizingsolver is selected from the group consisting of: linear programmingtools; heuristic engines; artificial intelligence techniques; andnon-linear optimization engines.
 18. A method for utilizing excessinventory of parts absent demand statement information, said parts usedin end products and having part identifiers, the method comprising:identifying an excess inventory of parts comprising part identifiers anda quantity associated with each part identifier; identifying potentialend products for manufacture comprising a Bill of Materials (BOM) foreach end product and where each BOM calls out at least one partidentifier in the excess inventory of parts; and determining a buildplan comprising one or more of the potential end products, the buildplan optimized to non-demand criteria and utilizing an amount of theexcess inventory.
 19. The method of claim 18, further comprising a costvalue associated with each part identifier and wherein the non-demandcriteria comprise a scalar value representing a ratio of the dollaramount spent to purchase additional parts in order to consume onedollar's worth of the excess inventory.
 20. The method of claim 18wherein the non-demand criteria comprise a criterion selected from thegroup consisting of: maximizing the quantity of the excess inventoryutilized; maximizing the quantity of the excess inventory utilizedwithout exceeding a specific dollar value of additional parts purchasedto produce the build plan; and minimizing the amount of additional moneyspent in order to utilize the amount of the excess inventory.
 21. Themethod of claim 18 further comprising a cost value associated with eachpart identifier and wherein the non-demand criteria comprise a criterionselected from the group consisting of: maximizing the total cost valueof the excess inventory utilized; and maximizing the total cost value ofthe excess inventory utilized without exceeding a specific dollar valueof additional parts purchased to produce the build plan.
 22. The methodof claim 18 further comprising profitability information on eachpotential end product and wherein the non-demand criteria comprisemaximizing the overall profit of the build plan.
 23. The method of claim18 further comprising business impact information and wherein thenon-demand criteria comprise taking into account the business impact ofthe build plan.
 24. The method of claim 18 wherein the build plan isdetermined using an optimizing solver.
 25. The method of claim 24wherein the optimizing solver is selected from the group consisting of:linear programming tools; heuristic engines; artificial intelligencetechniques; and non-linear optimization engines.
 26. A storage mediumcomprising machine readable computer program code for utilizing excessinventory in a manufacturing environment, said excess inventorycomprising parts used in end products, said storage medium includinginstructions for a causing a computer to implement a method, comprising:translating sales specific terminology describing said end products intobill of material terminology describing said parts used in end productsvia a bill of material structure; and utilizing said bill of materialstructure, determining an optimal build plan for end items that, ifbuilt, would consume a desired quantity and/or type of excess inventory.27. The storage medium of claim 26, wherein said translating salesspecific terminology into said bill of material terminology includes:classifying features associated with said end items according to partsrequired to build said end items.
 28. The storage medium of claim 27,wherein said classifying features associated with said end itemsincludes: sub-classifying said features wherein a feature of an end itemcomprises more than one distinct set of parts.
 29. The storage medium ofclaim 26, wherein said determining an optimal build plan includes:formulating constraints related to usage of parts in producing end itemsutilizing: data provided in said bill of material structure; andmanufacturing process data resulting in at least one saleable end item,said manufacturing process data comprising at least one of: costs;revenue data; inventory data; usage rates; yields; capacities; cycletimes; and alternate parts; and optimizing said constraints utilizing atleast one of: heuristics; linear programming; artificial intelligence;and non-linear optimization.
 30. The storage medium of claim 29, whereinselecting an end item from a list of saleable end items capable ofconsuming excess inventory includes: utilizing user-supplied pricinginformation to determine which of said saleable end items, if built,would consume the most excess parts while requiring minimal additionalexpense.
 31. The storage medium of claim 29, wherein selecting an enditem from a list of saleable items capable of consuming excess inventorycomprises: applying an algorithm comprising: k*ei; wherein k is a scalarfactor referring to a selectable number operable for expressing an upperlimit on how much to spend on additional parts in order to use up onedollar of excess inventory; and wherein further, ‘ei’ represents anamount in dollars of excess inventory consumed when producing one unitof an item ‘i’.
 32. A storage medium comprising machine readablecomputer program code for utilizing excess inventory of parts absentdemand statement information, said parts used in end products and havingpart identifiers, said storage medium including instructions for acausing a computer to implement a method comprising: identifying anexcess inventory of parts comprising part identifiers and a quantityassociated with each part identifier; identifying potential end productsfor manufacture comprising a Bill of Materials (BOM) for each endproduct and where each BOM calls out at least one part identifier in theexcess inventory of parts; and determining a build plan comprising oneor more of the potential end products, the build plan optimized tonon-demand criteria and utilizing an amount of the excess inventory. 33.The storage medium of claim 32, further comprising instructions forcausing the computer to implement a cost value associated with each partidentifier and wherein the non-demand criteria comprise a scalar valuerepresenting a ratio of the dollar amount spent to purchase additionalparts in order to consume one dollar's worth of the excess inventory.34. The storage medium of claim 32 wherein the non-demand criteriacomprise a criterion selected from the group consisting of: maximizingthe quantity of the excess inventory utilized; maximizing the quantityof the excess inventory utilized without exceeding a specific dollarvalue of additional parts purchased to produce the build plan; andminimizing the amount of additional money spent in order to utilize theamount of the excess inventory.
 35. The storage medium of claim 32further comprising instructions for causing the computer to implement acost value associated with each part identifier and wherein thenon-demand criteria comprise a criterion selected from the groupconsisting of: maximizing the total cost value of the excess inventoryutilized; and maximizing the total cost value of the excess inventoryutilized without exceeding a specific dollar value of additional partspurchased to produce the build plan.
 36. The storage medium of claim 32further comprising instructions for causing the computer to implementprofitability information on each potential end product and wherein thenon-demand criteria comprise maximizing the overall profit of the buildplan.
 37. The storage medium of claim 32 further comprising instructionsfor causing the computer to implement business impact information andwherein the non-demand criteria comprise taking into account thebusiness impact of the build plan.
 38. The storage medium of claim 32wherein the build plan is determined using an optimizing solver.
 39. Thestorage medium of claim 38 wherein the optimizing solver is selectedfrom the group consisting of: linear programming tools; heuristicengines; artificial intelligence techniques; and non-linear optimizationengines.
 40. A system for utilizing excess inventory in a manufacturingenvironment, said excess inventory comprising parts used in endproducts, the system comprising: an MRP engine; an inventory utilizationtool accessible to said MRP engine, said inventory utilization toolcomprising: a translation component; and a solution component; at leastone excess inventory file containing part numbers and correspondingquantities of excess parts held in inventory; at least one database ofmanufacturing process data, said manufacturing process data comprising:costs; revenue data; inventory data; usage rates; yields; capacities;cycle times; and alternate parts; a database of bills of material files;and a report database; wherein upon said inventory utilization tooltranslates sales specific terminology describing said end products intobill of material terminology describing said parts used in end productsvia a bill of material structure, and utilizing said bill of materialstructure, determines an optimal build plan for end items that, ifbuilt, would consume a desired quantity and/or type of excess inventory.41. The system of claim 40, wherein said optimal build plan isdetermined by identifying which end products, if produced, will consumea greatest quantity of excess parts while requiring minimal additionalexpenditure for additional parts.